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contributor authorGan, Qintao
contributor authorLi, Yang
date accessioned2017-05-09T00:57:33Z
date available2017-05-09T00:57:33Z
date issued2013
identifier issn0022-0434
identifier otherds_135_06_061009.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/151375
description abstractIn this paper, the exponential synchronization problem for fuzzy CohenGrossberg neural networks with timevarying delays, stochastic noise disturbance, and reactiondiffusion effects are investigated. By introducing a novel LyapunovKrasovskii functional with the idea of delay partitioning, a periodically intermittent controller is developed to derive sufficient conditions ensuring the addressed neural networks to be exponentially synchronized in terms of pnorm. The results extend and improve upon earlier work. A numerical example is provided to show the effectiveness of the proposed theories.
publisherThe American Society of Mechanical Engineers (ASME)
titleExponential Synchronization of Stochastic Reaction Diffusion Fuzzy Cohen Grossberg Neural Networks With Time Varying Delays Via Periodically Intermittent Control
typeJournal Paper
journal volume135
journal issue6
journal titleJournal of Dynamic Systems, Measurement, and Control
identifier doi10.1115/1.4025157
journal fristpage61009
journal lastpage61009
identifier eissn1528-9028
treeJournal of Dynamic Systems, Measurement, and Control:;2013:;volume( 135 ):;issue: 006
contenttypeFulltext


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